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   "source": [
    "# CMEMS In-Situ data\n",
    "\n",
    "All CMEMS in-situ data are provided in a standardised netCDF format including QC flags.\n",
    "\n",
    "They are also free to use: \n",
    "\n",
    "*\"These data were collected and made freely available by the Copernicus project and the programs that contribute to it\"*\n",
    "\n",
    "Example downloaded from [CMEMS/EMODNET](https://www.emodnet-physics.eu/Map/platinfo/PIROOSDownload.aspx?PlatformID=13762)"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import xarray as xr\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
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     "output_type": "execute_result",
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       "<xarray.Dataset>\n",
       "Dimensions:      (DEPTH: 10, LATITUDE: 34797, LONGITUDE: 34797, POSITION: 34797, TIME: 34797)\n",
       "Coordinates:\n",
       "  * TIME         (TIME) datetime64[ns] 2015-10-01 ... 2020-11-07T07:50:00.000...\n",
       "  * LATITUDE     (LATITUDE) float32 55.01 55.01 55.01 ... 55.01 55.01 55.01\n",
       "  * LONGITUDE    (LONGITUDE) float32 13.15 13.15 13.15 ... 13.15 13.15 13.15\n",
       "Dimensions without coordinates: DEPTH, POSITION\n",
       "Data variables:\n",
       "    TIME_QC      (TIME) float32 ...\n",
       "    POSITION_QC  (POSITION) float32 ...\n",
       "    PSAL         (TIME, DEPTH) float64 ...\n",
       "    PSAL_QC      (TIME, DEPTH) float32 ...\n",
       "    TEMP         (TIME, DEPTH) float64 ...\n",
       "    TEMP_QC      (TIME, DEPTH) float32 ...\n",
       "    OSAT         (TIME, DEPTH) float64 ...\n",
       "    OSAT_QC      (TIME, DEPTH) float32 ...\n",
       "    DEPH         (TIME, DEPTH) float32 ...\n",
       "    DEPH_QC      (TIME, DEPTH) float32 ...\n",
       "Attributes:\n",
       "    naming_authority:               Copernicus Marine In Situ\n",
       "    ices_platform_code:             \n",
       "    area:                           Baltic Sea\n",
       "    format_version:                 1.4\n",
       "    contact:                        cmems-service@smhi.se\n",
       "    author:                         cmems-service\n",
       "    cdm_data_type:                  timeSeries\n",
       "    summary:                        Oceanographic data from the Baltic Sea. M...\n",
       "    references:                     http://marine.copernicus.eu http://www.ma...\n",
       "    data_assembly_center:           SMHI\n",
       "    wmo_inst_type:                  \n",
       "    doi:                            https://doi.org/10.13155/59938 https://do...\n",
       "    citation:                       These data were collected and made freely...\n",
       "    Conventions:                    CF-1.6 Copernicus-InSituTAC-FormatManual-...\n",
       "    bottom_depth:                    \n",
       "    qc_manual:                      Recommendations for in-situ data Near Rea...\n",
       "    distribution_statement:         These data follow Copernicus standards; t...\n",
       "    quality_index:                  A\n",
       "    comment:                        \n",
       "    netcdf_version:                 netCDF-4 classic model\n",
       "    source:                         mooring\n",
       "    geospatial_lon_min:             13.1542\n",
       "    quality_control_indicator:      1\n",
       "    history_version:                10\n",
       "    geospatial_lon_max:             13.1542\n",
       "    data_type:                      OceanSITES time-series data\n",
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       "    geospatial_vertical_min:        2.0000\n",
       "    time_coverage_end:              2020-11-07T07:50:00Z\n",
       "    id:                             BO_TS_MO_FINO2\n",
       "    update_interval:                P1M\n",
       "    last_date_observation:          2020-11-07T07:50:00Z\n",
       "    time_coverage_start:            2015-10-01T00:00:00Z\n",
       "    history:                        2019-06-25T13:00:30Z File created by SMHI...\n",
       "    geospatial_vertical_max:        20.0000\n",
       "    institution_references:         www.bsh.de\n",
       "    last_longitude_observation:     13.1542\n",
       "    pi_name:                        BSH\n",
       "    geospatial_lat_min:             55.0083\n",
       "    wmo_platform_code:              \n",
       "    geospatial_lat_max:             55.0083\n",
       "    institution_edmo_code:          1850\n",
       "    data_mode:                      R\n",
       "    site_code:                      FINO2\n",
       "    title:                          Global Ocean - In Situ Wave Observations ...\n",
       "    date_update:                    2020-12-17T13:31:41Z\n",
       "    platform_name:                  FINO2\n",
       "    last_latitude_observation:      55.0083\n",
       "    source_platform_category_code:  48\n",
       "    institution:                    BSH"
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LONGITUDE    (LONGITUDE) float32 13.15 13.15 13.15 ... 13.15 13.15 13.15\nDimensions without coordinates: DEPTH, POSITION\nData variables:\n    TIME_QC      (TIME) float32 1.0 1.0 1.0 1.0 1.0 1.0 ... 1.0 1.0 1.0 1.0 1.0\n    POSITION_QC  (POSITION) float32 7.0 7.0 7.0 7.0 7.0 ... 1.0 1.0 1.0 1.0 1.0\n    PSAL         (TIME, DEPTH) float64 ...\n    PSAL_QC      (TIME, DEPTH) float32 ...\n    TEMP         (TIME, DEPTH) float64 ...\n    TEMP_QC      (TIME, DEPTH) float32 ...\n    OSAT         (TIME, DEPTH) float64 ...\n    OSAT_QC      (TIME, DEPTH) float32 ...\n    DEPH         (TIME, DEPTH) float32 ...\n    DEPH_QC      (TIME, DEPTH) float32 ...\nAttributes:\n    naming_authority:               Copernicus Marine In Situ\n    ices_platform_code:             \n    area:                           Baltic Sea\n    format_version:                 1.4\n    contact:                        cmems-service@smhi.se\n    author:                         cmems-service\n    cdm_data_type:                  timeSeries\n    summary:                        Oceanographic data from the Baltic Sea. M...\n    references:                     http://marine.copernicus.eu http://www.ma...\n    data_assembly_center:           SMHI\n    wmo_inst_type:                  \n    doi:                            https://doi.org/10.13155/59938 https://do...\n    citation:                       These data were collected and made freely...\n    Conventions:                    CF-1.6 Copernicus-InSituTAC-FormatManual-...\n    bottom_depth:                    \n    qc_manual:                      Recommendations for in-situ data Near Rea...\n    distribution_statement:         These data follow Copernicus standards; t...\n    quality_index:                  A\n    comment:                        \n    netcdf_version:                 netCDF-4 classic model\n    source:                         mooring\n    geospatial_lon_min:             13.1542\n    quality_control_indicator:      1\n    history_version:                10\n    geospatial_lon_max:             13.1542\n    data_type:                      OceanSITES time-series data\n    platform_code:                  FINO2\n    geospatial_vertical_min:        2.0000\n    time_coverage_end:              2020-11-07T07:50:00Z\n    id:                             BO_TS_MO_FINO2\n    update_interval:                P1M\n    last_date_observation:          2020-11-07T07:50:00Z\n    time_coverage_start:            2015-10-01T00:00:00Z\n    history:                        2019-06-25T13:00:30Z File created by SMHI...\n    geospatial_vertical_max:        20.0000\n    institution_references:         www.bsh.de\n    last_longitude_observation:     13.1542\n    pi_name:                        BSH\n    geospatial_lat_min:             55.0083\n    wmo_platform_code:              \n    geospatial_lat_max:             55.0083\n    institution_edmo_code:          1850\n    data_mode:                      R\n    site_code:                      FINO2\n    title:                          Global Ocean - In Situ Wave Observations ...\n    date_update:                    2020-12-17T13:31:41Z\n    platform_name:                  FINO2\n    last_latitude_observation:      55.0083\n    source_platform_category_code:  48\n    institution:                    BSH</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-6a298796-3a94-4fd5-9faf-317dd1a6c1ca' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6a298796-3a94-4fd5-9faf-317dd1a6c1ca' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span>DEPTH</span>: 10</li><li><span class='xr-has-index'>LATITUDE</span>: 34797</li><li><span class='xr-has-index'>LONGITUDE</span>: 34797</li><li><span>POSITION</span>: 34797</li><li><span class='xr-has-index'>TIME</span>: 34797</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-28b853b5-1243-4edd-abce-d5dea80761d8' class='xr-section-summary-in' type='checkbox'  checked><label for='section-28b853b5-1243-4edd-abce-d5dea80761d8' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>TIME</span></div><div class='xr-var-dims'>(TIME)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2015-10-01 ... 2020-11-07T07:50:...</div><input id='attrs-407ad264-08ec-4b3b-b83b-19a9af7ee921' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-407ad264-08ec-4b3b-b83b-19a9af7ee921' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8672e2be-7f38-4b5b-9987-033e628f6363' class='xr-var-data-in' type='checkbox'><label for='data-8672e2be-7f38-4b5b-9987-033e628f6363' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>valid_max :</span></dt><dd>90000.0</dd><dt><span>uncertainty :</span></dt><dd></dd><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>valid_min :</span></dt><dd>-90000.0</dd><dt><span>ancillary_variables :</span></dt><dd>TIME_QC</dd><dt><span>comment :</span></dt><dd></dd><dt><span>QC_indicator :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2015-10-01T00:00:00.000000000&#x27;, &#x27;2015-10-01T00:10:00.000000000&#x27;,\n       &#x27;2015-10-01T00:20:00.000000256&#x27;, ..., &#x27;2020-11-07T07:30:00.000000000&#x27;,\n       &#x27;2020-11-07T07:40:00.000000000&#x27;, &#x27;2020-11-07T07:50:00.000000256&#x27;],\n      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>LATITUDE</span></div><div class='xr-var-dims'>(LATITUDE)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>55.01 55.01 55.01 ... 55.01 55.01</div><input id='attrs-70a2192c-4a4a-4720-9340-817be77582fc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-70a2192c-4a4a-4720-9340-817be77582fc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-426ace82-e003-4215-8d8b-41de82725b2c' class='xr-var-data-in' type='checkbox'><label for='data-426ace82-e003-4215-8d8b-41de82725b2c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>uncertainty :</span></dt><dd></dd><dt><span>long_name :</span></dt><dd>Latitude of each location</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>ancillary_variables :</span></dt><dd>POSITION_QC</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd><dt><span>comment :</span></dt><dd></dd><dt><span>QC_indicator :</span></dt><dd>1</dd><dt><span>units :</span></dt><dd>degree_north</dd></dl></div><div class='xr-var-data'><pre>array([55.0083, 55.0083, 55.0083, ..., 55.0083, 55.0083, 55.0083],\n      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>LONGITUDE</span></div><div class='xr-var-dims'>(LONGITUDE)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>13.15 13.15 13.15 ... 13.15 13.15</div><input id='attrs-9ec153ec-b783-406c-936d-a8a897baf708' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9ec153ec-b783-406c-936d-a8a897baf708' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-63eb2284-10f0-4a0f-bedd-9ee151d939dd' class='xr-var-data-in' type='checkbox'><label for='data-63eb2284-10f0-4a0f-bedd-9ee151d939dd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>valid_max :</span></dt><dd>180.0</dd><dt><span>uncertainty :</span></dt><dd></dd><dt><span>long_name :</span></dt><dd>Longitude of each location</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>ancillary_variables :</span></dt><dd>POSITION_QC</dd><dt><span>valid_min :</span></dt><dd>-180.0</dd><dt><span>comment :</span></dt><dd></dd><dt><span>QC_indicator :</span></dt><dd>1</dd><dt><span>units :</span></dt><dd>degree_east</dd></dl></div><div class='xr-var-data'><pre>array([13.1542, 13.1542, 13.1542, ..., 13.1542, 13.1542, 13.1542],\n      dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-62afa96d-6cb0-4f77-9396-d494801fc41c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-62afa96d-6cb0-4f77-9396-d494801fc41c' class='xr-section-summary' >Data variables: <span>(10)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>TIME_QC</span></div><div class='xr-var-dims'>(TIME)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-e42969d4-05b5-4126-9798-c8fc12d5bf1e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e42969d4-05b5-4126-9798-c8fc12d5bf1e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-16db7f4d-312d-4af2-839c-65cb104decee' class='xr-var-data-in' type='checkbox'><label for='data-16db7f4d-312d-4af2-839c-65cb104decee' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>conventions :</span></dt><dd>Copernicus Marine In Situ reference table 2</dd><dt><span>valid_max :</span></dt><dd>9</dd><dt><span>long_name :</span></dt><dd>Time quality flag</dd><dt><span>flag_meanings :</span></dt><dd>no_qc_performed good_data probably_good_data bad_data_that_are_potentially_correctable bad_data value_changed not_used nominal_value interpolated_value missing_value</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>flag_values :</span></dt><dd>[0 1 2 3 4 5 6 7 8 9]</dd></dl></div><div class='xr-var-data'><pre>array([1., 1., 1., ..., 1., 1., 1.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>POSITION_QC</span></div><div class='xr-var-dims'>(POSITION)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-7f888503-203b-471b-a1a9-22751ff144fb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7f888503-203b-471b-a1a9-22751ff144fb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d4d3877f-9698-4d54-b0c8-e5b33bc2c662' class='xr-var-data-in' type='checkbox'><label for='data-d4d3877f-9698-4d54-b0c8-e5b33bc2c662' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>conventions :</span></dt><dd>Copernicus Marine In Situ reference table 2</dd><dt><span>valid_max :</span></dt><dd>9</dd><dt><span>long_name :</span></dt><dd>Position quality flag</dd><dt><span>flag_meanings :</span></dt><dd>no_qc_performed good_data probably_good_data bad_data_that_are_potentially_correctable bad_data value_changed not_used nominal_value interpolated_value missing_value</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>flag_values :</span></dt><dd>[0 1 2 3 4 5 6 7 8 9]</dd></dl></div><div class='xr-var-data'><pre>array([7., 7., 7., ..., 1., 1., 1.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PSAL</span></div><div class='xr-var-dims'>(TIME, DEPTH)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b0a127a7-5cd0-4725-a8ea-6fd959082c18' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b0a127a7-5cd0-4725-a8ea-6fd959082c18' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4fdcc723-0b20-4e0a-a589-cf9e8fef63d3' class='xr-var-data-in' type='checkbox'><label for='data-4fdcc723-0b20-4e0a-a589-cf9e8fef63d3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>valid_max :</span></dt><dd>40000</dd><dt><span>long_name :</span></dt><dd>Practical salinity</dd><dt><span>standard_name :</span></dt><dd>sea_water_practical_salinity</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>units :</span></dt><dd>0.001</dd><dt><span>data_mode :</span></dt><dd>R</dd></dl></div><div class='xr-var-data'><pre>[347970 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PSAL_QC</span></div><div class='xr-var-dims'>(TIME, DEPTH)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-769dde3d-5779-4167-95dc-5a02be8aae63' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-769dde3d-5779-4167-95dc-5a02be8aae63' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1cf095cc-bd5f-42b1-86a1-1efc469ab35b' class='xr-var-data-in' type='checkbox'><label for='data-1cf095cc-bd5f-42b1-86a1-1efc469ab35b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>valid_max :</span></dt><dd>9</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>conventions :</span></dt><dd>Copernicus Marine In Situ reference table 2</dd><dt><span>long_name :</span></dt><dd>Practical salinity quality flag</dd><dt><span>flag_meanings :</span></dt><dd>no_qc_performed good_data probably_good_data bad_data_that_are_potentially_correctable bad_data value_changed not_used nominal_value interpolated_value missing_value</dd><dt><span>flag_values :</span></dt><dd>[0 1 2 3 4 5 6 7 8 9]</dd></dl></div><div class='xr-var-data'><pre>[347970 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TEMP</span></div><div class='xr-var-dims'>(TIME, DEPTH)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3aa9303b-b204-4011-8427-9e5b6ae4de24' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3aa9303b-b204-4011-8427-9e5b6ae4de24' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e3877a57-4106-4b46-9d66-24b308a470dc' class='xr-var-data-in' type='checkbox'><label for='data-e3877a57-4106-4b46-9d66-24b308a470dc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>valid_max :</span></dt><dd>32000</dd><dt><span>long_name :</span></dt><dd>Sea temperature</dd><dt><span>standard_name :</span></dt><dd>sea_water_temperature</dd><dt><span>valid_min :</span></dt><dd>-2000</dd><dt><span>units :</span></dt><dd>degrees_C</dd><dt><span>data_mode :</span></dt><dd>R</dd></dl></div><div class='xr-var-data'><pre>[347970 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TEMP_QC</span></div><div class='xr-var-dims'>(TIME, DEPTH)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-dd3e56cf-54f9-4e15-8d39-a2366c766b5e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dd3e56cf-54f9-4e15-8d39-a2366c766b5e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7f624074-010b-42a6-89e0-5fd82f167834' class='xr-var-data-in' type='checkbox'><label for='data-7f624074-010b-42a6-89e0-5fd82f167834' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>valid_max :</span></dt><dd>9</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>conventions :</span></dt><dd>Copernicus Marine In Situ reference table 2</dd><dt><span>long_name :</span></dt><dd>Sea temperature quality flag</dd><dt><span>flag_meanings :</span></dt><dd>no_qc_performed good_data probably_good_data bad_data_that_are_potentially_correctable bad_data value_changed not_used nominal_value interpolated_value missing_value</dd><dt><span>flag_values :</span></dt><dd>[0 1 2 3 4 5 6 7 8 9]</dd></dl></div><div class='xr-var-data'><pre>[347970 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>OSAT</span></div><div class='xr-var-dims'>(TIME, DEPTH)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-290816ee-b98e-46d4-a37b-a259a637c8c4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-290816ee-b98e-46d4-a37b-a259a637c8c4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5e6f0dc6-30a7-45b0-90d2-e149c9a694a1' class='xr-var-data-in' type='checkbox'><label for='data-5e6f0dc6-30a7-45b0-90d2-e149c9a694a1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>valid_max :</span></dt><dd>10000</dd><dt><span>long_name :</span></dt><dd>Oxygen saturation</dd><dt><span>standard_name :</span></dt><dd>fractional_saturation_of_oxygen_in_sea_water</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>data_mode :</span></dt><dd>R</dd></dl></div><div class='xr-var-data'><pre>[347970 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>OSAT_QC</span></div><div class='xr-var-dims'>(TIME, DEPTH)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-148403ce-ce2e-471c-a382-4d4c91712231' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-148403ce-ce2e-471c-a382-4d4c91712231' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6af62209-80ba-49c4-bc4c-f7023370a1b3' class='xr-var-data-in' type='checkbox'><label for='data-6af62209-80ba-49c4-bc4c-f7023370a1b3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>valid_max :</span></dt><dd>9</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>conventions :</span></dt><dd>Copernicus Marine In Situ reference table 2</dd><dt><span>long_name :</span></dt><dd>Oxygen saturation quality flag</dd><dt><span>flag_meanings :</span></dt><dd>no_qc_performed good_data probably_good_data bad_data_that_are_potentially_correctable bad_data value_changed not_used nominal_value interpolated_value missing_value</dd><dt><span>flag_values :</span></dt><dd>[0 1 2 3 4 5 6 7 8 9]</dd></dl></div><div class='xr-var-data'><pre>[347970 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>DEPH</span></div><div class='xr-var-dims'>(TIME, DEPTH)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c407cebc-4110-401d-8913-eb395750d3b9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c407cebc-4110-401d-8913-eb395750d3b9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-31b2ca7a-504d-4700-8d8a-d28749cb98d9' class='xr-var-data-in' type='checkbox'><label for='data-31b2ca7a-504d-4700-8d8a-d28749cb98d9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>valid_max :</span></dt><dd>12000.0</dd><dt><span>long_name :</span></dt><dd>Depth</dd><dt><span>standard_name :</span></dt><dd>depth</dd><dt><span>valid_min :</span></dt><dd>-12000.0</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>ancillary_variables :</span></dt><dd>DEPH_QC</dd><dt><span>uncertainty :</span></dt><dd></dd><dt><span>reference :</span></dt><dd>sea_level</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>data_mode :</span></dt><dd>R</dd></dl></div><div class='xr-var-data'><pre>[347970 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>DEPH_QC</span></div><div class='xr-var-dims'>(TIME, DEPTH)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f0f6d4bf-8335-4ba9-85e4-d55807af1f21' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f0f6d4bf-8335-4ba9-85e4-d55807af1f21' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7a38bb60-ba28-4d22-9489-8e6efc1f2f16' class='xr-var-data-in' type='checkbox'><label for='data-7a38bb60-ba28-4d22-9489-8e6efc1f2f16' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>valid_max :</span></dt><dd>9</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>conventions :</span></dt><dd>Copernicus Marine In Situ reference table 2</dd><dt><span>long_name :</span></dt><dd>Depth quality flag</dd><dt><span>flag_meanings :</span></dt><dd>no_qc_performed good_data probably_good_data bad_data_that_are_potentially_correctable bad_data value_changed not_used nominal_value interpolated_value missing_value</dd><dt><span>flag_values :</span></dt><dd>[0 1 2 3 4 5 6 7 8 9]</dd></dl></div><div class='xr-var-data'><pre>[347970 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-49403484-41f6-4302-b525-d590e55de83b' class='xr-section-summary-in' type='checkbox'  ><label for='section-49403484-41f6-4302-b525-d590e55de83b' class='xr-section-summary' >Attributes: <span>(50)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>naming_authority :</span></dt><dd>Copernicus Marine In Situ</dd><dt><span>ices_platform_code :</span></dt><dd></dd><dt><span>area :</span></dt><dd>Baltic Sea</dd><dt><span>format_version :</span></dt><dd>1.4</dd><dt><span>contact :</span></dt><dd>cmems-service@smhi.se</dd><dt><span>author :</span></dt><dd>cmems-service</dd><dt><span>cdm_data_type :</span></dt><dd>timeSeries</dd><dt><span>summary :</span></dt><dd>Oceanographic data from the Baltic Sea. Measured properties: the hydrographic conditions as currents, temperature and salinity.</dd><dt><span>references :</span></dt><dd>http://marine.copernicus.eu http://www.marineinsitu.eu</dd><dt><span>data_assembly_center :</span></dt><dd>SMHI</dd><dt><span>wmo_inst_type :</span></dt><dd></dd><dt><span>doi :</span></dt><dd>https://doi.org/10.13155/59938 https://doi.org/10.13155/40846 https://doi.org/10.13155/53381 https://doi.org/10.13155/36230 https://doi.org/10.13155/43494</dd><dt><span>citation :</span></dt><dd>These data were collected and made freely available by the Copernicus project and the programs that contribute to it</dd><dt><span>Conventions :</span></dt><dd>CF-1.6 Copernicus-InSituTAC-FormatManual-1.41 Copernicus-InSituTAC-SRD-1.5 Copernicus-InSituTAC-ParametersList-3.2.0</dd><dt><span>bottom_depth :</span></dt><dd> </dd><dt><span>qc_manual :</span></dt><dd>Recommendations for in-situ data Near Real Time Quality Control https://doi.org/10.13155/36230</dd><dt><span>distribution_statement :</span></dt><dd>These data follow Copernicus standards; they are public and free of charge. User assumes all risk for use of data. User must display citation in any publication or product using data. User must contact PI prior to any commercial use of data.</dd><dt><span>quality_index :</span></dt><dd>A</dd><dt><span>comment :</span></dt><dd></dd><dt><span>netcdf_version :</span></dt><dd>netCDF-4 classic model</dd><dt><span>source :</span></dt><dd>mooring</dd><dt><span>geospatial_lon_min :</span></dt><dd>13.1542</dd><dt><span>quality_control_indicator :</span></dt><dd>1</dd><dt><span>history_version :</span></dt><dd>10</dd><dt><span>geospatial_lon_max :</span></dt><dd>13.1542</dd><dt><span>data_type :</span></dt><dd>OceanSITES time-series data</dd><dt><span>platform_code :</span></dt><dd>FINO2</dd><dt><span>geospatial_vertical_min :</span></dt><dd>2.0000</dd><dt><span>time_coverage_end :</span></dt><dd>2020-11-07T07:50:00Z</dd><dt><span>id :</span></dt><dd>BO_TS_MO_FINO2</dd><dt><span>update_interval :</span></dt><dd>P1M</dd><dt><span>last_date_observation :</span></dt><dd>2020-11-07T07:50:00Z</dd><dt><span>time_coverage_start :</span></dt><dd>2015-10-01T00:00:00Z</dd><dt><span>history :</span></dt><dd>2019-06-25T13:00:30Z File created by SMHI Baltic Sea PU.\n2019-06-28T19:43:43Z Data converted by SMHI Baltic Sea PU.\n2019-11-12T08:04:13Z Data converted by SMHI Baltic Sea PU.\n2019-11-18T19:30:44Z Data converted by SMHI Baltic Sea PU.\n2020-01-09T13:30:48Z Data converted by SMHI Baltic Sea PU.\n2020-05-11T13:24:43Z Data converted by SMHI Baltic Sea PU.\n2020-05-29T07:31:37Z Data converted by SMHI Baltic Sea PU.\n2020-05-29T13:32:04Z Data converted by SMHI Baltic Sea PU.\n2020-12-01T13:47:43Z Data converted by SMHI Baltic Sea PU.\n2020-12-17T13:31:41Z Data converted by SMHI Baltic Sea PU.</dd><dt><span>geospatial_vertical_max :</span></dt><dd>20.0000</dd><dt><span>institution_references :</span></dt><dd>www.bsh.de</dd><dt><span>last_longitude_observation :</span></dt><dd>13.1542</dd><dt><span>pi_name :</span></dt><dd>BSH</dd><dt><span>geospatial_lat_min :</span></dt><dd>55.0083</dd><dt><span>wmo_platform_code :</span></dt><dd></dd><dt><span>geospatial_lat_max :</span></dt><dd>55.0083</dd><dt><span>institution_edmo_code :</span></dt><dd>1850</dd><dt><span>data_mode :</span></dt><dd>R</dd><dt><span>site_code :</span></dt><dd>FINO2</dd><dt><span>title :</span></dt><dd>Global Ocean - In Situ Wave Observations Re-Analysis</dd><dt><span>date_update :</span></dt><dd>2020-12-17T13:31:41Z</dd><dt><span>platform_name :</span></dt><dd>FINO2</dd><dt><span>last_latitude_observation :</span></dt><dd>55.0083</dd><dt><span>source_platform_category_code :</span></dt><dd>48</dd><dt><span>institution :</span></dt><dd>BSH</dd></dl></div></li></ul></div></div>"
     },
     "metadata": {},
     "execution_count": 2
    }
   ],
   "source": [
    "ds = xr.open_dataset(\"../tests/data/BO_TS_MO_FINO2.nc\")\n",
    "ds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "'These data were collected and made freely available by the Copernicus project and the programs that contribute to it'"
      ]
     },
     "metadata": {},
     "execution_count": 3
    }
   ],
   "source": [
    "ds.attrs['citation']"
   ]
  },
  {
   "source": [
    "## Quality flags"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "   qc_flag                                    meaning\n",
       "0        0                            no_qc_performed\n",
       "1        1                                  good_data\n",
       "2        2                         probably_good_data\n",
       "3        3  bad_data_that_are_potentially_correctable\n",
       "4        4                                   bad_data\n",
       "5        5                              value_changed\n",
       "6        6                                   not_used\n",
       "7        7                              nominal_value\n",
       "8        8                         interpolated_value\n",
       "9        9                              missing_value"
      ],
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>qc_flag</th>\n      <th>meaning</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>0</td>\n      <td>no_qc_performed</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>1</td>\n      <td>good_data</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>2</td>\n      <td>probably_good_data</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>3</td>\n      <td>bad_data_that_are_potentially_correctable</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>4</td>\n      <td>bad_data</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>5</td>\n      <td>value_changed</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>6</td>\n      <td>not_used</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>7</td>\n      <td>nominal_value</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>8</td>\n      <td>interpolated_value</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>9</td>\n      <td>missing_value</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "metadata": {},
     "execution_count": 4
    }
   ],
   "source": [
    "pd.DataFrame({'qc_flag' : ds.PSAL_QC.flag_values,\n",
    "    'meaning' : ds.PSAL_QC.flag_meanings.split()})"
   ]
  },
  {
   "source": [
    "# Salinity\n",
    "\n",
    "Lets's see if we have some outliers..."
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
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291.085144 75.609606 \r\nL 291.200559 75.440943 \r\nL 291.533227 75.440943 \r\nL 291.621486 75.103618 \r\nL 291.641853 75.440943 \r\nL 291.675799 75.440943 \r\nL 291.764057 75.609606 \r\nL 291.784425 75.440943 \r\nL 291.831949 75.440943 \r\nL 291.947364 75.609606 \r\nL 291.967731 75.609606 \r\nL 291.974521 75.440943 \r\nL 292.076358 75.609606 \r\nL 292.571964 75.609606 \r\nL 292.660223 75.27228 \r\nL 292.68738 75.440943 \r\nL 292.707747 75.440943 \r\nL 292.823162 75.27228 \r\nL 292.850319 75.27228 \r\nL 292.986101 74.59763 \r\nL 293.094728 74.59763 \r\nL 293.23051 75.440943 \r\nL 293.244089 75.103618 \r\nL 293.257667 75.27228 \r\nL 293.522443 75.27228 \r\nL 293.529232 75.103618 \r\nL 293.631069 75.27228 \r\nL 293.78043 75.27228 \r\nL 293.827954 75.440943 \r\nL 293.889056 75.27228 \r\nL 294.466133 75.27228 \r\nL 294.581548 75.103618 \r\nL 294.819167 75.103618 \r\nL 294.887059 74.934955 \r\nL 294.927794 75.27228 \r\nL 294.948161 75.103618 \r\nL 295.016052 75.778269 \r\nL 295.022841 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142.084035 60.092634 \r\nL 142.179083 72.911002 \r\nL 142.314865 74.428967 \r\nL 142.3556 74.428967 \r\nL 142.504961 72.742339 \r\nL 142.532118 73.585653 \r\nL 142.586431 70.043736 \r\nL 142.620376 71.730363 \r\nL 142.600009 69.537747 \r\nL 142.6679 69.70641 \r\nL 142.681479 68.019783 \r\nL 142.742581 71.055712 \r\nL 142.762948 71.055712 \r\nL 142.776527 71.055712 \r\nL 142.837629 71.393038 \r\nL 142.885153 71.224375 \r\nL 142.898731 70.887049 \r\nL 142.973411 71.899026 \r\nL 143.102405 72.405014 \r\nL 143.211031 70.043736 \r\nL 143.129561 72.573677 \r\nL 143.258555 70.212398 \r\nL 143.278922 71.393038 \r\nL 143.346814 67.007806 \r\nL 143.353603 70.381061 \r\nL 143.448651 63.634552 \r\nL 143.475807 65.827167 \r\nL 143.489386 64.309203 \r\nL 143.496175 68.019783 \r\nL 143.584433 66.164493 \r\nL 143.788107 73.248328 \r\nL 143.794897 73.248328 \r\nL 143.903523 74.260304 \r\nL 143.937468 74.091641 \r\nL 144.066462 72.742339 \r\nL 144.073251 72.911002 \r\nL 144.100408 71.5617 \r\nL 144.168299 66.670481 \r\nL 144.202245 72.573677 \r\nL 144.215823 69.369085 \r\nL 144.276925 72.405014 \r\nL 144.324449 70.887049 \r\nL 144.378762 69.369085 \r\nL 144.460232 70.212398 \r\nL 144.467021 70.381061 \r\nL 144.494177 68.357108 \r\nL 144.521334 69.031759 \r\nL 144.534912 69.031759 \r\nL 144.636749 69.200422 \r\nL 144.575647 68.694434 \r\nL 144.643538 69.031759 \r\nL 144.684273 68.694434 \r\nL 144.677484 69.200422 \r\nL 144.758953 68.863096 \r\nL 144.833634 69.369085 \r\nL 144.874369 69.200422 \r\nL 144.881158 69.200422 \r\nL 145.064464 67.345132 \r\nL 145.071254 67.345132 \r\nL 145.139145 66.839144 \r\nL 145.186669 67.176469 \r\nM 147.175885 67.345132 \r\nL 147.223409 65.99583 \r\nL 147.298089 66.333155 \r\nL 147.325246 66.164493 \r\nL 147.365981 67.176469 \r\nL 147.37277 67.176469 \r\nL 147.461029 67.345132 \r\nL 147.481396 67.176469 \r\nL 147.488185 67.176469 \r\nL 147.657913 65.658504 \r\nL 147.75975 66.164493 \r\nL 147.780118 65.99583 \r\nL 147.807274 65.99583 \r\nL 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113.121592 42.889035 \r\nL 113.230218 37.829153 \r\nL 113.189483 47.948917 \r\nL 113.237007 38.166478 \r\nL 113.366001 44.575662 \r\nL 113.29132 36.479851 \r\nL 113.399947 42.383047 \r\nL 113.474627 39.009792 \r\nL 113.522151 39.347118 \r\nL 113.535729 39.347118 \r\nL 113.542518 39.178455 \r\nL 113.603621 39.853106 \r\nL 113.644355 39.347118 \r\nL 113.691879 39.853106 \r\nL 113.76656 39.684443 \r\nL 113.827662 38.503804 \r\nL 113.84124 39.853106 \r\nL 113.895553 38.672467 \r\nL 113.902342 38.672467 \r\nL 113.983812 37.829153 \r\nL 114.017758 37.997816 \r\nL 114.099227 38.841129 \r\nL 114.119595 37.997816 \r\nL 114.187486 36.648514 \r\nL 114.173908 38.166478 \r\nL 114.194275 36.817177 \r\nL 114.31648 45.756302 \r\nL 114.323269 45.756302 \r\nL 114.459051 47.611592 \r\nL 114.621991 49.804207 \r\nL 114.635569 49.298219 \r\nL 114.812086 45.418976 \r\nL 114.873189 45.756302 \r\nL 114.927502 46.26229 \r\nL 114.961447 44.744325 \r\nL 114.968236 44.744325 \r\nL 115.165121 35.973863 \r\nL 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144.996573 68.188446 \r\nL 145.118778 66.839144 \r\nL 145.186669 67.345132 \r\nM 147.175885 67.176469 \r\nL 147.223409 65.827167 \r\nL 147.304878 65.99583 \r\nL 147.352402 65.827167 \r\nL 147.467818 67.345132 \r\nL 147.637546 65.827167 \r\nL 147.651124 65.827167 \r\nL 147.664703 65.658504 \r\nL 147.698648 65.99583 \r\nL 147.752961 65.99583 \r\nL 147.814063 65.99583 \r\nL 147.909111 66.839144 \r\nL 147.936268 66.501818 \r\nL 148.099207 65.152516 \r\nL 148.173888 65.152516 \r\nL 148.289303 65.321179 \r\nL 148.296092 65.321179 \r\nL 148.350405 65.152516 \r\nL 148.363983 65.489842 \r\nL 148.397929 65.489842 \r\nL 148.425085 65.489842 \r\nL 148.486188 65.321179 \r\nL 148.540501 65.658504 \r\nL 148.588025 65.658504 \r\nL 148.70344 65.827167 \r\nL 148.730596 65.827167 \r\nL 148.846012 65.658504 \r\nL 148.852801 65.658504 \r\nL 148.866379 65.827167 \r\nL 148.94106 65.489842 \r\nL 148.954638 65.489842 \r\nL 148.975005 65.489842 \r\nL 149.117577 66.501818 \r\nL 149.185468 65.99583 \r\nL 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106.08805 49.635545 \r\nL 106.101628 47.442929 \r\nL 106.176309 54.020776 \r\nL 106.183098 54.020776 \r\nL 106.189887 54.189438 \r\nL 106.237411 53.177462 \r\nL 106.305302 50.984846 \r\nL 106.346037 52.671474 \r\nL 106.352826 52.671474 \r\nL 106.461452 53.008799 \r\nL 106.468241 52.840137 \r\nL 106.48182 52.840137 \r\nL 106.495398 53.177462 \r\nL 106.529344 52.502811 \r\nL 106.597235 53.008799 \r\nL 106.604024 53.008799 \r\nL 106.624392 52.671474 \r\nL 106.665126 53.346125 \r\nL 106.699072 53.346125 \r\nL 106.705861 53.346125 \r\nL 106.8688 54.695427 \r\nL 106.882379 54.695427 \r\nL 106.936692 54.864089 \r\nL 106.970637 54.358101 \r\nL 107.10642 53.68345 \r\nL 107.113209 53.68345 \r\nL 107.215046 52.840137 \r\nL 107.235414 53.177462 \r\nL 107.384774 54.189438 \r\nL 107.391564 54.189438 \r\nL 107.520557 52.165486 \r\nL 107.561292 52.671474 \r\nL 107.724231 54.020776 \r\nL 107.744599 54.020776 \r\nL 107.826068 54.864089 \r\nL 107.853225 54.020776 \r\nL 107.860014 53.852113 \r\nL 107.927905 54.526764 \r\nL 107.955062 54.189438 \r\nL 107.961851 54.189438 \r\nL 107.995796 54.020776 \r\nL 108.05011 54.695427 \r\nL 108.070477 54.695427 \r\nL 108.158736 56.719379 \r\nL 108.185892 55.370078 \r\nL 108.219838 56.044729 \r\nL 108.314886 53.177462 \r\nL 108.321675 53.177462 \r\nL 108.355621 53.852113 \r\nL 108.471036 51.153509 \r\nL 108.525349 50.816184 \r\nL 108.552505 51.322172 \r\nL 108.566084 51.153509 \r\nL 108.613608 53.177462 \r\nL 108.661132 50.984846 \r\nL 108.667921 51.659497 \r\nL 108.783336 43.732349 \r\nL 108.803703 46.768278 \r\nL 108.925908 52.502811 \r\nL 108.980221 51.82816 \r\nL 109.027745 46.768278 \r\nL 109.000588 52.671474 \r\nL 109.102425 48.454905 \r\nL 109.278943 53.852113 \r\nL 109.156738 47.442929 \r\nL 109.306099 53.177462 \r\nL 109.319677 53.346125 \r\nL 109.387569 52.502811 \r\nL 109.394358 52.671474 \r\nL 109.401147 52.671474 \r\nL 109.543719 51.82816 \r\nL 109.557297 51.82816 \r\nL 109.631978 48.792231 \r\nL 109.659134 48.960894 \r\nL 109.679502 56.888042 \r\nL 109.781339 55.370078 \r\nL 109.788128 56.382054 \r\nL 109.815284 47.780254 \r\nL 109.84923 49.804207 \r\nL 110.00538 43.395023 \r\nL 110.012169 44.238337 \r\nL 110.08685 41.37107 \r\nL 110.107217 43.057698 \r\nL 110.120795 43.057698 \r\nL 110.209054 40.190431 \r\nL 110.141163 43.395023 \r\nL 110.243 41.033745 \r\nL 110.433095 49.466882 \r\nL 110.439884 49.466882 \r\nL 110.453463 49.635545 \r\nL 110.528143 48.960894 \r\nL 110.596035 48.454905 \r\nL 110.623191 48.960894 \r\nL 110.78613 51.659497 \r\nL 110.969437 53.514787 \r\nL 110.989804 53.514787 \r\nL 111.050906 53.68345 \r\nL 111.064485 52.840137 \r\nL 111.071274 52.840137 \r\nL 111.200267 42.383047 \r\nL 111.25458 43.226361 \r\nL 111.26137 46.093627 \r\nL 111.349628 37.491827 \r\nL 111.356417 37.66049 \r\nL 111.397152 36.142526 \r\nL 111.519357 32.431945 \r\nL 111.532935 32.600608 \r\nL 111.580459 31.588632 \r\nL 111.716242 28.215377 \r\nL 111.600826 32.600608 \r\nL 111.750187 28.38404 \r\nL 111.763765 28.552702 \r\nL 111.838446 28.215377 \r\nL 111.858813 28.38404 \r\nL 111.865602 28.38404 \r\nL 111.899548 28.215377 \r\nL 111.940283 29.058691 \r\nL 111.947072 29.564679 \r\nL 112.008174 28.38404 \r\nL 112.04212 29.396016 \r\nL 112.048909 28.552702 \r\nL 112.130379 31.082643 \r\nL 112.27295 34.287235 \r\nL 112.300107 34.118573 \r\nL 112.388366 34.455898 \r\nL 112.558094 31.925957 \r\nL 112.59204 32.09462 \r\nL 112.598829 32.09462 \r\nL 112.612407 31.925957 \r\nL 112.680298 32.431945 \r\nL 112.687088 32.431945 \r\nL 112.816081 33.275259 \r\nL 112.82287 33.106596 \r\nL 112.829659 33.106596 \r\nL 112.90434 35.8052 \r\nL 112.965442 35.636537 \r\nL 113.006177 37.491827 \r\nL 113.094436 34.287235 \r\nL 113.189483 36.648514 \r\nL 113.264164 36.142526 \r\nL 113.29811 35.636537 \r\nL 113.325266 37.66049 \r\nL 113.366001 41.539733 \r\nL 113.440681 38.503804 \r\nL 113.522151 38.166478 \r\nL 113.549308 38.335141 \r\nL 113.678301 39.347118 \r\nL 113.712247 39.51578 \r\nL 113.752982 39.009792 \r\nL 113.773349 39.009792 \r\nL 113.861608 38.335141 \r\nL 113.902342 38.503804 \r\nL 113.915921 38.503804 \r\nL 114.031336 37.66049 \r\nL 114.051703 37.829153 \r\nL 114.106016 37.829153 \r\nL 114.248588 33.443922 \r\nL 114.302901 34.624561 \r\nL 114.431895 47.274266 \r\nL 114.31648 34.455898 \r\nL 114.47263 47.105603 \r\nL 114.601623 49.298219 \r\nL 114.608412 49.129556 \r\nL 114.615201 49.129556 \r\nL 114.642358 47.442929 \r\nL 114.723828 36.985839 \r\nL 114.757773 38.841129 \r\nL 114.866399 43.901011 \r\nL 114.900345 43.563686 \r\nL 115.008971 39.178455 \r\nL 114.934291 43.901011 \r\nL 115.036128 40.021769 \r\nL 115.056495 40.696419 \r\nL 115.117597 37.491827 \r\nL 115.484211 17.252299 \r\nL 115.572469 18.432938 \r\nL 139.918301 61.610599 \r\nL 139.945458 61.441936 \r\nL 140.00656 60.092634 \r\nL 140.067662 61.104611 \r\nL 140.108397 61.441936 \r\nL 140.16271 60.935948 \r\nL 140.183078 60.767285 \r\nL 140.250969 61.273273 \r\nL 140.271336 60.935948 \r\nL 140.298493 60.935948 \r\nL 140.488589 62.959901 \r\nL 140.644739 61.779262 \r\nL 140.78731 62.622575 \r\nL 140.807678 62.622575 \r\nL 140.916304 61.779262 \r\nL 140.936671 61.947924 \r\nL 141.004563 62.622575 \r\nL 141.038508 61.610599 \r\nL 141.052087 61.610599 \r\nL 141.147135 60.42996 \r\nL 141.174291 60.598622 \r\nL 141.255761 61.441936 \r\nL 141.208237 60.261297 \r\nL 141.276128 60.767285 \r\nL 141.384754 60.092634 \r\nL 141.33723 61.273273 \r\nL 141.391543 60.261297 \r\nL 141.398332 60.261297 \r\nL 141.411911 59.923971 \r\nL 141.466224 60.935948 \r\nL 141.473013 60.935948 \r\nL 141.49338 61.441936 \r\nL 141.588428 61.273273 \r\nL 141.703843 60.935948 \r\nL 141.832837 62.116587 \r\nL 141.880361 60.598622 \r\nL 141.927885 62.116587 \r\nL 141.934674 62.791238 \r\nL 141.995776 59.417983 \r\nL 142.002565 59.755309 \r\nL 142.077246 59.080658 \r\nL 142.104402 59.417983 \r\nL 142.3556 74.428967 \r\nL 142.362389 74.260304 \r\nL 142.382757 74.260304 \r\nL 142.586431 66.501818 \r\nL 142.722213 62.28525 \r\nL 142.735792 62.791238 \r\nL 142.810472 67.85112 \r\nL 142.857996 65.658504 \r\nL 142.90552 61.441936 \r\nL 142.980201 63.803214 \r\nL 143.054881 71.055712 \r\nL 143.109194 68.357108 \r\nL 143.122772 69.70641 \r\nL 143.14314 63.128563 \r\nL 143.177085 64.477865 \r\nL 143.204242 67.513795 \r\nL 143.278922 63.128563 \r\nL 143.285712 65.152516 \r\nL 143.333235 62.116587 \r\nL 143.380759 62.116587 \r\nL 143.502964 61.779262 \r\nL 143.509753 61.779262 \r\nL 143.625168 62.453913 \r\nL 143.638746 62.28525 \r\nL 143.659114 62.28525 \r\nL 143.774529 62.622575 \r\nL 143.781318 62.453913 \r\nL 143.815264 63.971877 \r\nL 143.917101 73.079665 \r\nL 143.957836 69.537747 \r\nL 143.964625 70.043736 \r\nL 144.018938 65.99583 \r\nL 144.025727 66.333155 \r\nL 144.120775 65.321179 \r\nL 144.154721 65.658504 \r\nL 144.249768 68.694434 \r\nL 144.310871 66.839144 \r\nL 144.399129 65.321179 \r\nL 144.405919 66.670481 \r\nL 144.426286 69.031759 \r\nL 144.494177 64.983854 \r\nL 144.507756 65.827167 \r\nL 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65.152516 \r\nL 143.183875 61.610599 \r\nL 143.244977 63.297226 \r\nL 143.333235 61.610599 \r\nL 143.401127 62.116587 \r\nL 143.407916 62.116587 \r\nL 143.523331 61.779262 \r\nL 143.652325 62.28525 \r\nL 143.69306 62.28525 \r\nL 143.808475 62.453913 \r\nL 143.815264 62.453913 \r\nL 143.930679 67.513795 \r\nL 144.052884 65.658504 \r\nL 144.059673 65.658504 \r\nL 144.134353 65.321179 \r\nL 144.16151 65.827167 \r\nL 144.168299 65.827167 \r\nL 144.249768 67.007806 \r\nL 144.276925 65.99583 \r\nL 144.412708 64.983854 \r\nL 144.426286 65.99583 \r\nL 144.494177 64.646528 \r\nL 144.521334 65.321179 \r\nL 144.541701 64.983854 \r\nL 144.575647 65.99583 \r\nL 144.609593 65.658504 \r\nL 144.731797 67.682457 \r\nL 144.792899 67.176469 \r\nL 144.779321 68.863096 \r\nL 144.813267 68.188446 \r\nL 144.854001 68.863096 \r\nL 144.915104 67.682457 \r\nL 144.996573 67.85112 \r\nL 145.030519 67.345132 \r\nL 145.071254 67.513795 \r\nL 145.105199 67.007806 \r\nL 145.125567 67.007806 \r\nL 145.152723 67.007806 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149.294095 65.827167 \r\nL 149.341618 65.658504 \r\nM 188.26372 72.573677 \r\nL 188.270509 70.718387 \r\nL 188.284087 71.730363 \r\nL 256.250101 73.922979 \r\nL 256.25689 74.59763 \r\nL 256.317992 71.5617 \r\nL 256.33836 71.899026 \r\nL 256.351938 72.067688 \r\nL 256.426618 71.393038 \r\nL 256.460564 71.055712 \r\nL 256.508088 71.5617 \r\nL 256.521666 71.5617 \r\nL 256.664238 75.609606 \r\nL 256.671027 73.922979 \r\nL 256.766075 72.742339 \r\nL 256.772864 74.260304 \r\nL 256.779653 74.260304 \r\nL 256.861123 75.609606 \r\nL 256.80681 72.405014 \r\nL 256.901858 75.440943 \r\nL 256.96296 73.754316 \r\nL 256.983327 76.958908 \r\nL 256.996906 76.958908 \r\nL 257.03764 76.284257 \r\nL 257.085164 77.296233 \r\nL 257.227736 75.609606 \r\nL 257.241314 76.115594 \r\nL 257.248104 76.958908 \r\nL 257.315995 74.091641 \r\nL 257.343151 75.440943 \r\nL 257.451778 71.5617 \r\nL 257.465356 72.911002 \r\nL 257.478934 72.911002 \r\nL 257.499302 72.236351 \r\nL 257.560404 74.428967 \r\nL 257.573982 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261.233325 65.321179 \r\nL 261.240114 64.477865 \r\nL 261.253692 66.501818 \r\nL 261.355529 65.827167 \r\nL 261.43021 64.14054 \r\nL 261.396264 67.176469 \r\nL 261.457366 66.333155 \r\nL 261.572782 68.863096 \r\nL 261.477734 65.152516 \r\nL 261.613516 67.682457 \r\nL 261.640673 66.839144 \r\nL 261.647462 69.200422 \r\nL 268.565589 71.730363 \r\nL 268.653848 67.345132 \r\nL 290.467333 69.70641 \r\nL 290.528435 69.875073 \r\nL 290.542013 69.031759 \r\nL 290.732109 62.453913 \r\nL 290.752477 66.164493 \r\nL 290.854314 71.224375 \r\nL 290.793211 65.321179 \r\nL 290.874681 69.031759 \r\nL 290.96294 66.501818 \r\nL 290.990096 66.670481 \r\nL 291.153035 63.634552 \r\nL 291.207349 64.477865 \r\nL 291.220927 64.309203 \r\nL 291.438179 61.779262 \r\nL 291.492492 62.116587 \r\nL 291.621486 64.815191 \r\nL 291.648642 64.477865 \r\nL 291.675799 65.99583 \r\nL 291.696166 65.827167 \r\nL 291.838738 70.043736 \r\nL 291.988099 67.176469 \r\nL 291.994888 67.345132 \r\nL 292.001677 68.357108 \r\nL 292.062779 65.152516 \r\nL 292.096725 65.99583 \r\nL 292.103514 65.827167 \r\nL 292.144249 67.176469 \r\nL 292.151038 67.007806 \r\nL 292.198562 68.357108 \r\nL 292.422603 67.682457 \r\nL 292.517651 70.549724 \r\nL 292.558386 70.043736 \r\nL 292.60591 67.176469 \r\nL 292.673801 68.863096 \r\nL 292.68738 68.525771 \r\nL 292.870686 71.224375 \r\nL 292.972523 69.537747 \r\nL 292.931788 71.730363 \r\nL 292.992891 70.212398 \r\nL 293.006469 70.549724 \r\nL 293.053993 69.70641 \r\nL 293.101517 70.212398 \r\nL 293.142252 68.357108 \r\nL 293.196565 70.381061 \r\nL 293.210143 70.043736 \r\nL 293.257667 71.5617 \r\nL 293.38666 69.70641 \r\nL 293.407028 70.212398 \r\nL 293.427395 72.236351 \r\nL 293.488497 68.188446 \r\nL 293.515654 70.381061 \r\nL 293.569967 69.200422 \r\nL 293.62428 70.212398 \r\nL 293.665015 72.742339 \r\nL 293.746484 71.730363 \r\nL 293.875478 68.525771 \r\nL 293.923002 70.212398 \r\nL 293.895845 67.682457 \r\nL 293.984104 69.200422 \r\nL 293.990893 69.200422 \r\nL 294.072363 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296.007266 66.164493 \r\nL 296.068368 63.634552 \r\nL 296.109103 64.14054 \r\nL 296.319566 64.646528 \r\nL 296.333144 63.803214 \r\nL 296.414614 66.164493 \r\nL 296.543607 64.983854 \r\nL 296.428192 66.333155 \r\nL 296.550396 65.489842 \r\nL 296.713336 69.031759 \r\nL 296.720125 68.694434 \r\nL 296.726914 68.525771 \r\nL 296.740492 70.212398 \r\nL 296.801594 73.079665 \r\nL 296.869486 72.911002 \r\nL 296.896642 73.41699 \r\nL 296.978112 67.682457 \r\nL 297.012058 68.188446 \r\nL 297.018847 68.188446 \r\nL 297.066371 68.357108 \r\nL 297.086738 67.682457 \r\nL 297.297201 71.5617 \r\nL 297.30399 71.224375 \r\nL 297.432984 66.333155 \r\nL 297.473719 65.99583 \r\nL 297.582345 67.345132 \r\nL 297.643447 65.152516 \r\nL 297.684182 67.513795 \r\nL 297.69776 67.176469 \r\nL 297.704549 67.176469 \r\nL 297.792808 71.899026 \r\nL 297.718127 65.489842 \r\nL 297.806386 71.5617 \r\nL 297.921801 73.585653 \r\nL 297.928591 73.585653 \r\nL 297.962536 73.248328 \r\nL 298.037217 73.754316 \r\nL 298.308782 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\n"
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "source": [
    "ds.PSAL.sel(TIME=slice(\"2020\",\"2021\")).plot.line(x='TIME');\n"
   ]
  },
  {
   "source": [
    "Qualtity flags indicates not all values are good ()"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<Figure size 432x288 with 1 Axes>",
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     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "source": [
    "ds.PSAL_QC.sel(TIME=slice(\"2020\",\"2021\")).plot.line(x='TIME');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "metadata": {},
     "execution_count": 7
    },
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<Figure size 432x288 with 1 Axes>",
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     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "source": [
    "pd.Series(ds.PSAL_QC.sel(TIME=slice(\"2020\",\"2021\")).values.astype(np.int32).flatten()).value_counts().plot.bar() # simple on-liner to get distriution of values"
   ]
  },
  {
   "source": [
    "Most values have a qc-flag ==1 (good data). But some have 2,3,4, which are varying degrees of confidence that the data is bad."
   ],
   "cell_type": "markdown",
   "metadata": {}
  }
 ]
}